2024
Patient-Specific Heart Geometry Modeling for Solid Biomechanics Using Deep Learning
Pak D, Liu M, Kim T, Liang L, Caballero A, Onofrey J, Ahn S, Xu Y, McKay R, Sun W, Gleason R, Duncan J. Patient-Specific Heart Geometry Modeling for Solid Biomechanics Using Deep Learning. IEEE Transactions On Medical Imaging 2024, 43: 203-215. PMID: 37432807, PMCID: PMC10764002, DOI: 10.1109/tmi.2023.3294128.Peer-Reviewed Original ResearchMeSH KeywordsBiomechanical PhenomenaComputer SimulationDeep LearningHeartHumansPatient-Specific ModelingConceptsFinite element analysisDeep learning methodsSpatial accuracyElement analysisDeep learningStress estimationLearning methodsSimulation accuracyDeployment simulationHigh spatial accuracyThin structuresMesh generationVolumetric meshingDeformation energyGeometry modelingVolumetric meshMesh qualityElement qualitySimultaneous optimizationMain noveltyBiomechanics studiesMeshModeling characteristicsAccuracyDownstream analysis
2023
Deep learning of image-derived measures of body composition in pediatric, adolescent, and young adult lymphoma: association with late treatment effects
Tram N, Chou T, Janse S, Bobbey A, Audino A, Onofrey J, Stacy M. Deep learning of image-derived measures of body composition in pediatric, adolescent, and young adult lymphoma: association with late treatment effects. European Radiology 2023, 33: 6599-6607. PMID: 36988714, DOI: 10.1007/s00330-023-09587-z.Peer-Reviewed Original ResearchConceptsProportional hazards regression analysisHazards regression analysisLate effectsBody composition measuresAYA patientsHigh riskBody compositionCox proportional hazards regression analysisTreatment-related late effectsComposition measuresCancer treatmentSerious adverse eventsLate treatment effectsYoung adult patientsSubcutaneous adipose tissueRegression analysisCare CT imagesSingle-site studyMuscle tissueAdult patientsAdverse eventsInitial stagingPediatric patientsAdult lymphomasPrognostic valueDeep learning-based attenuation map generation with simultaneously reconstructed PET activity and attenuation and low-dose application
Shi L, Zhang J, Toyonaga T, Shao D, Onofrey J, Lu Y. Deep learning-based attenuation map generation with simultaneously reconstructed PET activity and attenuation and low-dose application. Physics In Medicine And Biology 2023, 68: 035014. PMID: 36584395, DOI: 10.1088/1361-6560/acaf49.Peer-Reviewed Original Research
2020
Deep learning-based attenuation map generation for myocardial perfusion SPECT
Shi L, Onofrey JA, Liu H, Liu YH, Liu C. Deep learning-based attenuation map generation for myocardial perfusion SPECT. European Journal Of Nuclear Medicine And Molecular Imaging 2020, 47: 2383-2395. PMID: 32219492, DOI: 10.1007/s00259-020-04746-6.Peer-Reviewed Original ResearchSparse Data–Driven Learning for Effective and Efficient Biomedical Image Segmentation
Onofrey JA, Staib LH, Huang X, Zhang F, Papademetris X, Metaxas D, Rueckert D, Duncan JS. Sparse Data–Driven Learning for Effective and Efficient Biomedical Image Segmentation. Annual Review Of Biomedical Engineering 2020, 22: 1-27. PMID: 32169002, PMCID: PMC9351438, DOI: 10.1146/annurev-bioeng-060418-052147.Peer-Reviewed Original Research
2019
An investigation of quantitative accuracy for deep learning based denoising in oncological PET
Lu W, Onofrey JA, Lu Y, Shi L, Ma T, Liu Y, Liu C. An investigation of quantitative accuracy for deep learning based denoising in oncological PET. Physics In Medicine And Biology 2019, 64: 165019. PMID: 31307019, DOI: 10.1088/1361-6560/ab3242.Peer-Reviewed Original Research
2018
Deep-learned placental vessel segmentation for intraoperative video enhancement in fetoscopic surgery
Sadda P, Imamoglu M, Dombrowski M, Papademetris X, Bahtiyar MO, Onofrey J. Deep-learned placental vessel segmentation for intraoperative video enhancement in fetoscopic surgery. International Journal Of Computer Assisted Radiology And Surgery 2018, 14: 227-235. PMID: 30484115, PMCID: PMC6438174, DOI: 10.1007/s11548-018-1886-4.Peer-Reviewed Original ResearchSegmenting the Brain Surface From CT Images With Artifacts Using Locally Oriented Appearance and Dictionary Learning
Onofrey JA, Staib LH, Papademetris X. Segmenting the Brain Surface From CT Images With Artifacts Using Locally Oriented Appearance and Dictionary Learning. IEEE Transactions On Medical Imaging 2018, 38: 596-607. PMID: 30176584, PMCID: PMC6476428, DOI: 10.1109/tmi.2018.2868045.Peer-Reviewed Original Research